Computer-aided extraction of semantics from keywords to confirm match of buyer offers to seller bids

ABSTRACT

One embodiment involves a method and apparatus for mapping lexical keywords into entity description semantics in order to create unambiguous buyer-confirmed descriptions of entities. The method described herein relies on a computer program and some mechanism for computer data storage.

RELATED APPLICATION(S)

This is a Continuation Application of U.S. patent application Ser. No.11/213,145, which was filed on Aug. 25, 2005, which in turn claimspriority from U.S. Provisional Application 60/606,357, filed Aug. 31,2004, which incorporated herein by reference.

BACKGROUND OF INVENTION

There are many descriptions of computer-aided searches of large searchspaces, such as the world wide web, whereby narrowing the search spaceto a successively smaller and more precise area of interest isaccomplished using one or more algorithms involving lexicons.

One problem with the use of lexicons is the limitation inherent in apure textual search. For example, although a lexical search of the worldwide web for matches to “blue sweater” might be refined throughhuman-computer interactions to the more specific “blue sweater crew neckmen's large”, the resulting search result set is likely to includecitations for:

-   (A) Descriptions of an article of men's apparel known as a sweater    and having elements of fashion known as a crew-neck and available in    size large and extra-large.-   (B) Descriptions of an article of men's apparel known as a sweater    and having elements of fashion known as a crew-neck and available at    large department stores.-   Many reprints and quotes from an often quoted article on the    hardworking men on the crew of the Blue Man Group and their    experiences during their tour of large cities.

In the above case, the intended search scope is best characterized bythe citation in item A. Item B is closer, however there was no semanticmeaning to the keyword “large” to indicate that “large” should be usedto modify the size of the article of apparel rather than to modify thesize of the department store. Item C is wildly out of scope as comparedto the buyers intended search space, yet scores a hit (match) on therefined search terms.

Even more sophisticated computer-aided lexical searches employinglexical associations do not appreciably and consistently reduce theoccurrences of search results returning citations that are wildlyoutside of the target scope (false hits). One commonly employed partialsolution to the shortcomings of a pure lexical search is to injectlexical associations into the lexical refinements. Prior attempts toinject lexical associations into computer-aided searches have relied onthe existence of a virtual expert advisor, or other access to adomain-specific knowledgebase. In practice such implementations merelyinject lexical associations iteratively, resulting in the constructionof longer and longer search strings. This technique can result in arapid narrowing of the search space, however this technique does notreliably eliminate or reduce the occurrence of false hits or wildly outof scope citations.

It has been observed that when humans interact with computer-aidedsearch engines (e.g., Google, eBay.com) in search of products, servicesor information, they frequently provide keywords that tend to be valuesor characteristics of the desired products, services or information. Forexample, when searching for an automobile, the keyword string might be:

-   -   “1997 Mustang red convertible”        where each of the above keywords is the value of an implied        attribute. A human would imply the following attributes;    -   Implied Attributes={Model_year, Model_name, Exterior_color,        Body_style}

Furthermore, a human would infer a mapping of the keywords to attributesas follows:

-   -   Mapping: {Model_year=1997,        -   Model_name=Mustang,        -   Exterior_color=red,        -   Body_style=convertible}

In use, a mapping between the human-specified values/characteristics andthe correct corresponding attribute is required in order to enable anunambiguous and effective (i.e., few or no false hits) computer-aidedsearch of a large structured data search space.

Thus, what is desired is a method and apparatus to confirm the mappingbetween the human-specified values/characteristics and the correctcorrespondence to characteristics found in an entity description (e.g.product, service, or information), among other techniques to overcomethe above prior art problems (as well as other prior art problems notmentioned).

SUMMARY

One embodiment involves a method and apparatus for mapping lexicalkeywords into entity description semantics in order to createunambiguous buyer-confirmed descriptions of entities. The methoddescribed herein relies on a computer program and some mechanism forcomputer data storage.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 depicts the process flow and data storage as is commonly used intext searches.

FIG. 2 depicts the data storage elements, processes and examples ofsemantic category extraction and category confirmation.

FIG. 3 depicts the data storage elements, process and examples ofsemantic attribute extraction and category attribute confirmation.

FIG. 4 depicts the data storage elements, process and examples ofsemantic attribute value extraction and category attribute valueconfirmation.

FIG. 5 depicts an example of a computer-parsable description ofhierarchical category description.

FIG. 6 depicts an example of a computer-parsable representation of anitem description.

FIG. 7 depicts an example of a computer-parsable representation of theranking of importance of an item attribute.

FIG. 8 depicts the key protocol exchanges between Server and Client.

FIG. 9 depicts examples of

-   -   a computer-parsable representation of Category Attribute DTD    -   a compressed format of the ITEMS ARRAY, and    -   an expansion of the ITEMS ARRAY into a textual/human-readable        format.

DETAILED DESCRIPTION

One method defined in the present embodiment may include the followinginputs

-   -   A list of one of more text strings (110) as have been provided        by the buyer as applicable to the search underway. This list may        contain one or more words specifically excluded as a result of        the lexical keyword refinement.    -   A database (210) containing the union of all known entity        category descriptions, which may occur as an enumerated list of        hierarchical category descriptions, or in a formal language that        permits computer-aided enumeration. An example using a        human-readable formal language to describe the levels of the        hierarchy is provided in FIG. 5.    -   A database (240) containing buyer profiles.    -   A database (350) containing entity descriptions. An example of        an entity description is given in FIG. 6.    -   A database (355) containing a relative scoring of entity        attributes. Such scoring is based on the empirical or        human-entered likelihood of a particular attribute being        important to a buyer in search of that entity. An example of        this scoring database is given in FIG. 7.

With these inputs then, the mapping front buyer-provided keywords tobuyer-confirmed product descriptions occurs through the client-serverprotocol exchanges of FIG. 8, and more specifically through applicationof the following operations:

Operation #1:

Given a list of one or inure text strings, possibly includingbuyer-excluded strings, the process (220) scores the quality of themapping of the text strings against each of the hierarchical categorydescription expansions. For example, given the strings “sweater largecrew NOT (children)” the process (220) may return a high score (i.e.,matching to hierarchical levels) for the following hierarchical categorydescriptions:

-   -   (A) apparel.men.outerwear.sweater (high score because two of the        given strings match)    -   (B) apparel.women.outerwear.sweater (lower score because only        one of the given strings match)

There is also a set of hierarchical category descriptions (e.g.,apparel.children.boy.outerwear.sweater) that may receive a low scoringof quality of match due to occurrence of one or more excluded wordsfound in the hierarchical category description.

Finally there is the set of hierarchical category descriptions thatreceive a zero score due to no matches of the strings found in thehierarchical category descriptions.

In one embodiment of this operation, words/strings that are known to beattribute values (e.g., names of colors) and are not likely to be foundin any hierarchical category description, are pre-screened from thescoring process, thus reducing compute time required for this operation.

In another embodiment of this operation, one of many scoring algorithmsis selected on the basis of the profile (e.g. record in database 240) ofa returning buyer, specifically the process 220 increases the score of aparticular category description if that category description had beenconfirmed by the buyer in a previous search. For example, a returningcustomer with the keyword string “box seat tickets” who had on previousoccasions purchased tickets for theatre performances would more likelysee theatre-related ticket categories at the top of the list rather thansay tickets for Hockey games.

Operation #2:

The highest scoring hierarchical category descriptions are presented tothe buyer in order of highest score toward lowest score. The buyer isthen given the opportunity to select the best match of the hierarchicalcategory description as compared to the entity the buyer seeks. In theexample:

-   -   apparel.men.outerwear.sweater    -   apparel.men.sportswear.sweater    -   apparel.men.holiday.sweater    -   apparel.women.outerwear.sweater    -   apparel.women.sportswear.sweater    -   apparel.women.holiday.sweater    -   apparel.children.outerwear.sweater    -   apparel.children.sportswear.sweater    -   apparel.children.holiday.sweater    -   entertainment.live-events.tickets.blue-man-group

In one embodiment of this operation, the number of entities in theentity database (350) that correspond to a particular category isdisplayed to the buyer, thus providing a technique of positive feedbackduring the search refinement. An example of this is shown in FIG. 2.

In another embodiment of this operation a logically contiguous set ofmatching categories (known as a category group) are selectivelycollapsed so as to reduce the number of enumerated matching categoriesto a smaller set and thus facilitate display to the buyer. In ourexample, “blue sweater” would match the following ten (10) fullyenumerated categories:

-   -   apparel.men.outerwear.sweater    -   apparel.men.sportswear.sweater    -   apparel.men.holiday.sweater    -   apparel.women.outerwear.sweater    -   apparel.women.sportswear.sweater    -   apparel.women.holiday.sweater    -   apparel.children.sportswear.sweater    -   apparel.children.sportswear.sweater    -   apparel.children.holiday.sweater    -   entertainment.live-events.tickets.blue-man-group

In order to display matched categories in a limited display space, wemay wish to collapse the categories. Observe that the first nine (9)fully enumerated categories belong to a category group. The collapsedset may thus be reduced to four (4) categories:

-   -   apparel.men . . . sweater <collapsed from outerwear, sportswear        and holiday>    -   apparel.women . . . sweater <collapsed from outerwear,        sportswear and holiday>    -   apparel.children . . . sweater <collapsed from outerwear,        sportswear and holiday>    -   entertainment.live-events.tickets.blue-man-group

In another embodiment of this operation, if a category group wascollapsed in order to reduce the number of matching categories, and thebuyer selects front among one or more collapsed category groups, thenext level(s) of expansion are presented to the buyer for confirmation.For example, if the buyer confirmed the collapsed category “apparel.men. . . sweater”, the corresponding fully enumerated categories arepresented for confirmation. Thus, following our example:

-   -   apparel.men.outerwear.sweater    -   apparel.men.sportswear.sweater    -   apparel.men.holiday.sweater

For the purpose of continuing with our example though the followingoperations, let us assume the buyer selects the category:

-   -   apparel.men.outerwear.sweater.

The buyer-selected category is stored in the storage (230) for use insubsequent operations.

Operation #3:

At the conclusion of Operation #2, the category description to thelowest level of hierarchy is known (that is, the category is known downto that level where no further hierarchical levels are defined). Withthis confirmed knowledge that the buyer intends to pursue a search forentities in the specified category, the process (360) makes suggestionsto the buyer of most important search parameters (i.e., attributes). Theorder of presentation to the buyer of the attributes is determined onthe basis of:

-   -   The frequency of occurrence of a particular entity attribute as        found in the entity descriptions database (350), and/or    -   The value of the Attribute Quotient Database entry for is        particular entity attribute (355)

The process (360) may scan entity entries found in the Entity Database(350) that are entities corresponding to the category selected inOperation #2. The process (360) may assemble and rank attributes foundin those entries and suggest to the buyer a set of attributes mostfrequently found. In the example, since the buyer selectedapparel.men.outerwear.sweater (during Operation #2), the set ofattributes displayed to the buyer would include:

-   -   {generic_color, size, generic_style, manufacturer_name,        manufacturer_product_name}.

In another embodiment, the Attribute Quotient Database entry for aparticular entity attribute is stored as an array whereby the index ofthe array corresponds to a particular class of buyer (e.g., anX-generation consumer, a Y-generation consumer, a business-to-businessbuyer) and each value in the array (i.e., the Attribute Quotient) isdetermined by behaviors or characteristics of the class of buyer. Forexample, Y-generation consumers statistically choose The Gap over otherdesigners, while X-generation consumers statistically prefer RalphLauren over other designers. The Attribute Quotient Database thusinfluences the ordering of Category Attributes and the Values of thoseCategory Attributes for presentation to the Buyer in Operation #4.

In one embodiment, the Server (810) of FIG. 8 sends to the Client (820)

-   -   a) structured text in a form similar to the Category Attribute        DTD (910) and    -   b) a computer representation of the Items Array (920).

Thus the Client is able to display the Items Array in a human-readableformat (930) using a graphical user interface as further described inOperation #4.

Operation #4:

The buyer is then provided a technique to rank the buyer's relativeimportance/ranking of the one or more attributes presented for thisparticular search.

In another embodiment of this Operation #4, one or more graphical userinterface devices are presented to the buyer in order to aid buyerranking of the relative importance of the attributes.

In another embodiment of this Operation #4, the buyer may be offered achoice to select from one or more predefined search parameters thatuniquely identify a product (e.g., SKU, or SKU plus color code).Alternatively, in one embodiment, the process 360 may suggest one ormore matching Featured Item, and offer the buyer the chance to purchasethe corresponding Featured Item.

In another embodiment, the attributes are displayed dynamically, whereeach successive click results in a new dynamically generated screen thatshows the buyer-selected ranking of the attributes. Multiple iterationsof buyer clicks followed by repainting of the screen result in a finaldynamically generated screen showing all of the buyer-selectedattributes in order of importance to the buyer.

At this point in Operation #4, the buyer has either confirmed buyer'sdesire to search for matching entities based on an exact match to a SKU(e.g., the buyer selected a Featured Item), or the buyer has confirmedthe relative importance of specific attributes in the parametric search.

In the Operation #4 process 420 the buyer is aided to identifyprioritized choices (1^(st) choice, 2^(nd) choice, etc.) of values orranges of values desired (e.g., the availability of a sweater in‘generic_color=blue’ is acceptable as a first choice and availability in‘generic_color=green’ is acceptable as a second choice).

In one embodiment, one or more graphical user interface device(s) arepresented to the buyer in order to aid buyer's selection of one or morevalues or ranges of values of attributes.

In another embodiment, the attribute values are displayed dynamically,where each successive click results in a new dynamically generatedscreen that shows the buyer-selected ranking at the attribute values.Multiple iterations of buyer clicks followed by repainting of the screenresults finally in a dynamically generated screen showing all of thebuyer-selected attribute values it order of importance to the buyer.

Operation #5:

At the conclusion of Operation #4, the buyer has either confirmed timeprecedence of attributes and has indicated preferred values on the basisof actual items available and/or indicated acceptable ranges of valuesof attributes. An organized array of matching items are presented to thebuyer for purchase, in the event the buyer elects not to conclude atransaction, the buyer is given the opportunity to ‘save’ the confirmedcriteria (possibly including acceptable ranges for certain attributevalues) for subsequent searches. The buyer is presented with options forcomputer-aided actions to be taken on behalf of the buyer in subsequentsearches.

In one embodiment, the buyer is given the opportunity to select one froma group of rule sets, each set containing the rules of exchangeincluding currency designation, exchange rate authority and limits, anda description of acceptable payment instruments (e.g., credit card,P.O., Paypal, etc).

In another embodiment, the buyer's search requirements can be stored ina computer memory and acted on or accessed at a later time. Futureaction by computer acting as agent for the buyer may inform the buyer ofa (newly identified) match or the computer acting as agent for the buyermay perform the transaction on behalf of the buyer.

Following are various optional features that may be optionally includedin various embodiments:

-   -   The method of FIG. 1 whereby the buyers keywords are filtered to        eliminate low value words such as articles (‘a’, ‘the’, ‘an’)        connectives and prepositions.    -   The method of FIG. 1 whereby in case of the presence of        unambiguous keywords, those keywords are mapped to synonyms        known to be in more common use (e.g. the words “clothing” gets        mapped to the synonym “apparel”.    -   The method of FIG. 1 whereby a match of the buyer's keywords to        category descriptions receive a higher score on the basis of        previous full or partial matches as may be recorded in the        buyer's profile record.    -   Category Descriptions of FIG. 2 whereby the hierarchy of the        category descriptions are described in XML    -   Category Descriptions of FIG. 2 whereby the hierarchy of the        category descriptions are organized as a map of a department        store.    -   Category Descriptions of FIG. 2 whereby the basic item        description is in the form of the AART Product XML dictionary.    -   A technique whereby the buyer is presented with a graphical user        interface page containing three (3) independent        frames/areas: (a) the text search area, (b) the        refinement/feedback area, and (e) the browsing/results area.    -   The method of FIG. 2 whereby the hierarchical/category        description is confirmed by the buyer using a graphical user        interface.    -   The method of FIG. 3 whereby the buyer can exit the parametric        search at any time and go directly to browsing mode (as        described in item ‘c’ above).    -   The method of FIG. 3 whereby item attributes (and a selection of        values) are proposed to the buyer on the basis of the frequency        of occurrence of an attribute being found among the union of        items in that confirmed category description.    -   The method of FIG. 4 whereby the Entity Description database        (350) contains the rules of exchange including currency        designation, exchange rate authority and limits, and a        description of acceptable payment instruments (e.g., credit        card, P.O., PayPal, etc.)    -   Search criteria/results derive guidance for next operation(s) in        the search process whereby at any point during execution of        processes 210, 310, 360, or 420 a list of products known to have        similar attributes to buyer's criteria are presented to buyer in        a browsable window or frame.    -   The method of FIG. 4 whereby the value or range of values Of an        attribute are confirmed by the buyer through a graphical use        interface.    -   The automatic generation of database 355 whereby the database is        generated over time, using actual search results and by capture        and analysis of actual buyers' behaviors.

Those skilled in the art may now recognize that the search space hasbeen reduced from the broad class of retrievable entities that may matchone or more text-only keywords, down to a search for one or moreentities that belong to a known, unambiguous and specific category, andfurther, that a match between the buyer's search criteria and entitiescan be made on the basis of a scoring system whereby an exact match isnot a necessary condition required before presenting the matchingentities to the buyer.

The invention claimed is:
 1. A server-implemented method of returningresults responsive to a search entered by a user throughcomputer-parsable graphical user interface pages, the method comprising:accessing, from stored first database records, category descriptions ofitems potentially responsive to the search, at least some of thecategory descriptions comprising two or more item attributes of arespective item; accessing from stored second database records, anentity description for at least some of the items potentially responsiveto the search, the entity description comprising at least one valueassigned to each item attribute of the two or more item attributes;executing at least a portion of a client-server protocol to send, over anetwork, a first computer-parsable graphical user interface pagedisplayable on a screen display of a client computer coupled to thenetwork, the first computer-parsable graphical user interface pagecomprising an interface to a search engine executing a computerizedsearch function, wherein the interface to the search engine has a textsearch area to capture user input constituting the search; performing alexical search on the user input constituting the search using thesearch engine to return search results from a search corpus accessibleby the search engine; executing at least another portion of theclient-server protocol to send a second computer-parsable graphical userinterface page to display at least some of the search results on theclient computer; receiving an input word list selection by the user,wherein at least one word of the selected input word list comprises avalue or a range of values of an attribute of the items potentiallyresponsive to the search; scoring at least some of the categorydescriptions, the scoring determined at least in part by mapping atleast one word of the selected input word list against correspondingentity descriptions to form a plurality of scored category descriptions,wherein an occurrence of one or more lexical matches constitutes amapping; sending a third computer-parsable graphical user interface pageto display at least some of the scored category descriptions based atleast in part on the mapping; receiving a selected category descriptionof the at least some of the scored category descriptions; sending afourth computer-parsable graphical user interface page to display, onthe client computer, suggested item attributes and suggested itemattribute values based at least in part on the selected categorydescription; receiving from the user, in response to the displayedsuggested item attributes, a selection of the suggested item attributevalues of the selected category description; iteratively displaying tothe user, after respective inputs from the user, a value or a range ofvalues for at least some of the suggested item attribute values of theselected category description until the user has selected one of apreferred value or acceptable range of values for at least some of thesuggested item attribute values, wherein at least some of the respectiveinputs by the user causes an iteration of the screen display of thepreferred value or the acceptable range of values; sending a fifthcomputer-parsable graphical user interface page to display, on theclient computer, matching items corresponding to at least some of thepreferred value or the acceptable range of values from the search corpusto enable selection by the user of a final selected item, wherein thematching items comprise at least a portion of the results responsive tothe search; and storing a preferred selection that the user chooses withrespect to one of a manufacturer or brand of the final selected item. 2.The method of claim 1 wherein one or more user selections comprises aconfirmation of iterative precedence of attributes by the user.
 3. Themethod of claim 1 further comprising: accessing, from stored thirddatabase records comprising at least the buyer profile, a plurality ofbuyer profiles for respective buyers, the buyer profiles comprising atleast a category description pertaining to a previous search by arespective buyer.
 4. The method of claim 1 further comprising increasingthe scoring of the at least some of the category descriptions based atleast in part on results of a previous search.
 5. The method of claim 1wherein the mapping is performed to a lowest level of categorydescriptions below which no further levels of category descriptions aredefined.
 6. The method of claim 1 further comprising: assigning acategory attribute quotient comprising a number for each value assignedto each item attribute, and storing each category attribute quotient inan array that is indexed against a behavior or characteristic of a classof user regarding the respective item attribute, and wherein thecategory attribute quotient for each value determines an ordering ofcategory attributes and respective values for display to the user. 7.The method of claim 1 wherein the graphical user interface pagecomprises a hypertext markup language (HTML)-based page accessible overthe network coupling the client computer to a server computer.
 8. Themethod of claim 7 wherein user input receiving steps are performed onthe client computer and the search engine is performed on the servercomputer.
 9. The method of claim 1 wherein the selection of thesuggested item attribute values of the selected category description isselected by the user in a specific order.
 10. The method of claim 1further comprising presenting, on the client computer, a browsing areadisplayed within the first computer-parsable graphical user interfacepage, wherein the browsing area is accessible at least upon exit of thesearch by the user.
 11. A physical, non-transitory computer readablemedium having stored thereon instructions that when executed by aprocessor-based computing device implement a server-based method ofreturning results responsive to a search entered by a user throughcomputer-parsable graphical user interface pages, comprising: accessing,from stored first database records, category descriptions of itemspotentially responsive to the search, at least some of the categorydescriptions comprising two or more item attributes of a respectiveitem; accessing, from stored second database records, an entitydescription for at least some of the items potentially responsive to thesearch, the entity description comprising at least one value assigned toeach item attribute of the two or more item attributes; executing atleast a portion of a client-server protocol to send, over a network, afirst computer-parsable graphical user interface page displayable on ascreen display of a client computer coupled to the network, a firstcomputer-parsable graphical user interface page; to present, on a clientcomputer the graphical user interface page, the first computer-parsablegraphical user interface page comprising an interface to a search engineexecuting a computerized search function, wherein the interface to thesearch engine has a text search area to capture user input constitutingthe search; performing a lexical search on the user input constitutingthe search using the search engine to return search results from asearch corpus accessible by the search engine; executing at leastanother portion of a client-server protocol to send a secondcomputer-parsable graphical user interface page to display at least someof the search results on the client computer; receiving an input wordlist selection by the user, wherein at least one word of the selectedinput word list comprises a value or a range of values of an attributeof the items potentially responsive to the search; scoring at least someof the category descriptions, the scoring determined at least in part bymapping at least one word of the selected input word list againstcorresponding entity descriptions to form a plurality of scored categorydescriptions, wherein an occurrence of one or more lexical matchesconstitutes a mapping; sending a third computer-parsable graphical userinterface page to display at least some of the scored categorydescriptions based at least in part on the mapping; receiving a selectedcategory description of the at least some of the scored categorydescriptions; sending a fourth computer-parsable graphical userinterface page to display, on the client computer, suggested itemattributes and suggested item attribute values based at least in part onthe selected category description; receiving from the user, in responseto the displayed suggested item attributes, a selection of the suggesteditem attribute values of the selected category description; iterativelydisplaying to the user, after respective inputs from the user, a valueor a range of values for at least some of the suggested item attributevalues of the selected category description until the user has selectedone of a preferred value or acceptable range of values for at least someof the suggested item attribute values, wherein at least some of therespective inputs by the user causes an iteration of the screen displayof the preferred value or the acceptable range of values; sending afifth computer-parsable graphical user interface page to display, on theclient computer, matching items corresponding to at least some of thepreferred value or the acceptable range of values from the search corpusto enable selection by the user of a final selected item wherein thematching items comprise at least a portion of the results responsive tothe search; and storing a preferred selection that the user chooses withrespect to one of a manufacturer or brand of the final selected item.12. A system for returning results responsive to a search entered by auser through computer-parsable graphical user interface pages, thesystem comprising: a server computer component, accessing, from storedfirst database records, category descriptions of items potentiallyresponsive to the search, at least some of the category descriptionscomprising two or more item attributes of a respective item andaccessing, from stored second database records, an entity descriptionfor at least some of the items potentially responsive to the search, theentity description comprising at least one value assigned to each itemattribute of the two or more item attributes; another server computercomponent executing at least a portion of a client-server protocol tosend, over a network, a first computer-parsable graphical user interfacepage displayable on a screen display of a client computer coupled to thenetwork, the first computer-parsable graphical user interface pagecomprising an interface to a search engine executing a computerizedsearch function, wherein the interface to the search engine has a textsearch area to capture user input constituting the search; a searchengine performing a lexical search on the user input constituting thesearch to return search results from a search corpus accessible by thesearch engine; a yet further server computer component executing atleast another portion of the client-server protocol to send a secondcomputer-parsable graphical user interface page to display at least someof the search results on the client computer, and receiving an inputword list selection by the user, wherein at least one word of theselected input word list comprises a value or a range of values of anattribute of the items potentially responsive to the search; yet anotherserver computer component scoring at least some of the categorydescriptions by, at least in part, mapping at least one word of theselected input word list against corresponding entity descriptions toform a plurality of scored category descriptions, wherein an occurrenceof one or more lexical matches constitutes a mapping; an interfacedevice sending a third computer-parsable graphical user interface pageto display at least some of the scored category descriptions based atleast in part on the mapping, receiving a selected category descriptionof the at least some of the scored category descriptions, and sending afourth computer-parsable graphical user interface page to display, onthe client computer, suggested item attributes and suggested itemattribute values based at least in part on the selected categorydescription; another interface device receiving from the user, inresponse to the displayed suggested item attributes, a selection of thesuggested item attribute values of the selected category description,iteratively displaying to the user, after respective inputs from theuser, a value or a range of values for at least some of the suggesteditem attribute values of the selected category description until theuser has selected one of a preferred value or acceptable range of valuesfor at least some of the suggested item attribute values, wherein atleast some of the respective inputs by the user causes an iteration ofthe screen display of the preferred value or the acceptable range ofvalues, and sending a fifth computer-parsable graphical user interfacepage to display, on the client computer, matching items corresponding toat least some of the preferred value or the acceptable range of valuesfrom the search corpus to enable selection by the user of a finalselected item, wherein the matching items comprise at least a portionthe results responsive to the search; and a computer data storagemechanism storing a preferred selection that the user chooses withrespect to one of a manufacturer or brand of the final selected item.13. The system of claim 12 wherein one or more user selections comprisesa confirmation of iterative precedence of attributes by the user. 14.The system of claim 12 wherein the server computer component accesses,from stored third database records comprising at least the buyerprofile, a plurality of buyer profiles for respective buyers, the buyerprofiles comprising at least a category description pertaining to aprevious search by a respective buyer.
 15. The system of claim 14wherein the server computer component increases the scoring of the atleast some of the category descriptions based at least in part onresults of a previous search.
 16. The system of claim 12 wherein themapping is performed to a lowest level of category descriptions belowwhich no further levels of category descriptions are defined.
 17. Thesystem of claim 12 wherein the server computer component assigns acategory attribute quotient comprising a number for each value assignedto each item attribute and stores each category attribute quotient in anarray that is indexed against a behavior or characteristic of a class ofuser regarding the respective item attribute, wherein the categoryattribute quotient for each value determines an ordering of categoryattributes and respective values for display to the user.
 18. The systemof claim 12 wherein the selection of the suggested item attribute valuesof the selected category description is selected by the user in aspecific order.
 19. The system of claim 12 wherein the computer-parsablegraphical user interface pages comprise at least some hypertext markuplanguage (HTML) that is presented, on the client computer, as a browsingarea.
 20. The system of claim 19, wherein the browsing area isaccessible at least upon exit of the search by the user.